Pub Date : 2023-10-20DOI: 10.51219/jaimld/jeremiah-ratican/17
Jeremiah Ratican, James Hutson, Daniel Plate
The paper aims to present a novel methodology for emulating the intricacies of human cognitive complexity by ingeniously integrating large language models with autonomous agents. Grounded in the theoretical framework of the modular mind theory-originally espoused by Fodor and later refined by scholars such as Joanna Bryson—the study seeks to venture into the untapped potential of large language models and autonomous agents in mirroring human cognition. Recent advancements in artificial intelligence, exemplified by the inception of autonomous agents like Age in GPT, auto GPT, and baby AGI, underscore the transformative capacities of these technologies in diverse applications. Moreover, empirical studies have substantiated that persona-driven autonomous agents manifest enhanced efficacy and nuanced performance, mimicking the intricate dynamics of human interactions. The paper postulates a theoretical framework incorporating persona-driven modules that emulate psychological functions integral to general cognitive processes. This framework advocates for the deployment of a plurality of autonomous agents, each informed by specific large language models, to act as surrogates for different cognitive functionalities. Neurological evidence is invoked to bolster the theoretical architecture, delineating how autonomous agents can serve as efficacious proxies for modular cognitive centers within the human brain. Given this foundation, a theory of mind predicated upon modular constructs offers a fertile landscape for further empirical investigations and technological innovations.
{"title":"Synthesizing Sentience: Integrating Large Language Models and Autonomous Agents for Emulating Human Cognitive Complexity","authors":"Jeremiah Ratican, James Hutson, Daniel Plate","doi":"10.51219/jaimld/jeremiah-ratican/17","DOIUrl":"https://doi.org/10.51219/jaimld/jeremiah-ratican/17","url":null,"abstract":"The paper aims to present a novel methodology for emulating the intricacies of human cognitive complexity by ingeniously integrating large language models with autonomous agents. Grounded in the theoretical framework of the modular mind theory-originally espoused by Fodor and later refined by scholars such as Joanna Bryson—the study seeks to venture into the untapped potential of large language models and autonomous agents in mirroring human cognition. Recent advancements in artificial intelligence, exemplified by the inception of autonomous agents like Age in GPT, auto GPT, and baby AGI, underscore the transformative capacities of these technologies in diverse applications. Moreover, empirical studies have substantiated that persona-driven autonomous agents manifest enhanced efficacy and nuanced performance, mimicking the intricate dynamics of human interactions. The paper postulates a theoretical framework incorporating persona-driven modules that emulate psychological functions integral to general cognitive processes. This framework advocates for the deployment of a plurality of autonomous agents, each informed by specific large language models, to act as surrogates for different cognitive functionalities. Neurological evidence is invoked to bolster the theoretical architecture, delineating how autonomous agents can serve as efficacious proxies for modular cognitive centers within the human brain. Given this foundation, a theory of mind predicated upon modular constructs offers a fertile landscape for further empirical investigations and technological innovations.","PeriodicalId":487259,"journal":{"name":"Journal of Artificial Intelligence Machine Learning and Data Science","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135666307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-16DOI: 10.51219/jaimld/yusuf-jazakallah/16
Yusuf Jazakallah
Bias in hiring algorithms is a critical issue that has been widely recognized in recent years. As more companies rely on automated candidate selection processes, it is essential to develop fair and equitable recruitment practices that ensure equal opportunities for all candidates. The objective of this research paper is to propose a comprehensive framework for mitigating bias in hiring algorithms. By utilizing a combination of machine learning techniques, statistical analysis, and ethical considerations, the study aims to identify, measure, and mitigate both overt and subtle forms of bias present in these algorithms. This paper's findings underscore the significance of employing de-biasing strategies to ensure diversity and inclusion in the workplace. In this introduction, we will discuss the critical issue of bias mitigation in hiring algorithms, the importance of fair and equitable recruitment practices, and the objective of the study. We will also provide an overview of the research methodology, the measurement of bias, and the proposed mitigation strategies. Finally, we will summarize the key findings and the proposed framework for reducing bias in hiring algorithms.
{"title":"Effective Strategies for Mitigating Bias in Hiring Algorithms: A Comparative Analysis","authors":"Yusuf Jazakallah","doi":"10.51219/jaimld/yusuf-jazakallah/16","DOIUrl":"https://doi.org/10.51219/jaimld/yusuf-jazakallah/16","url":null,"abstract":"Bias in hiring algorithms is a critical issue that has been widely recognized in recent years. As more companies rely on automated candidate selection processes, it is essential to develop fair and equitable recruitment practices that ensure equal opportunities for all candidates. The objective of this research paper is to propose a comprehensive framework for mitigating bias in hiring algorithms. By utilizing a combination of machine learning techniques, statistical analysis, and ethical considerations, the study aims to identify, measure, and mitigate both overt and subtle forms of bias present in these algorithms. This paper's findings underscore the significance of employing de-biasing strategies to ensure diversity and inclusion in the workplace. In this introduction, we will discuss the critical issue of bias mitigation in hiring algorithms, the importance of fair and equitable recruitment practices, and the objective of the study. We will also provide an overview of the research methodology, the measurement of bias, and the proposed mitigation strategies. Finally, we will summarize the key findings and the proposed framework for reducing bias in hiring algorithms.","PeriodicalId":487259,"journal":{"name":"Journal of Artificial Intelligence Machine Learning and Data Science","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136184260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-12DOI: 10.51219/jaimld/anastasios-liapakis/15
Zacharoula Smyrnaiou, Anastasios Liapakis, Anna Bougia
New Technologies in Primary and Secondary Education will be described using the examples of the proposed AI-tools. Finally, some recommendations and scenarios for responsible use of AI will be suggested in order to be used by policy makers and schools. The findings will be practical and significant, as not enough attention has been paid in Ethical use of AI in Primary and Secondary education.
{"title":"Ethical Use of Artificial Intelligence and New Technologies in Education 5.0","authors":"Zacharoula Smyrnaiou, Anastasios Liapakis, Anna Bougia","doi":"10.51219/jaimld/anastasios-liapakis/15","DOIUrl":"https://doi.org/10.51219/jaimld/anastasios-liapakis/15","url":null,"abstract":"New Technologies in Primary and Secondary Education will be described using the examples of the proposed AI-tools. Finally, some recommendations and scenarios for responsible use of AI will be suggested in order to be used by policy makers and schools. The findings will be practical and significant, as not enough attention has been paid in Ethical use of AI in Primary and Secondary education.","PeriodicalId":487259,"journal":{"name":"Journal of Artificial Intelligence Machine Learning and Data Science","volume":"294 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135967856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-30DOI: 10.51219/jaimld/debela-d-yadeta/14
Debela D. Yadeta, Adisu B. Bedane, Wesagn D. Chemma
:
{"title":"Human-Robot Interaction: A state of the art review","authors":"Debela D. Yadeta, Adisu B. Bedane, Wesagn D. Chemma","doi":"10.51219/jaimld/debela-d-yadeta/14","DOIUrl":"https://doi.org/10.51219/jaimld/debela-d-yadeta/14","url":null,"abstract":":","PeriodicalId":487259,"journal":{"name":"Journal of Artificial Intelligence Machine Learning and Data Science","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135040222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-11DOI: 10.51219/jaimld/jia-lin/13
He Jing, Zhong Qi, Jia Lin, He Jia, Liu Hongyan
layer is designed as the output wheel-rail force identification result. Taking the C80 vehicle as an example for analysis, the performance of the proposed method is evaluated from three aspects: model identification accuracy, generalization, and robustness. The results show that compared to traditional algorithms and single network models, the proposed method reduces the MSE value of wheel-rail lateral force identification by 44.4%~78.5%, and increases the R2 value by 1.3%~132.4%; the MSE value of wheel rail vertical force identification by 36%~75.9%, and the R2 value by 4.4%~87.9%. The proposed method can be applied to data of different working conditions and different noise levels.
{"title":"Wheel-Rail Force Identification Method Based on CNN-BiLSTM Hybrid Model","authors":"He Jing, Zhong Qi, Jia Lin, He Jia, Liu Hongyan","doi":"10.51219/jaimld/jia-lin/13","DOIUrl":"https://doi.org/10.51219/jaimld/jia-lin/13","url":null,"abstract":"layer is designed as the output wheel-rail force identification result. Taking the C80 vehicle as an example for analysis, the performance of the proposed method is evaluated from three aspects: model identification accuracy, generalization, and robustness. The results show that compared to traditional algorithms and single network models, the proposed method reduces the MSE value of wheel-rail lateral force identification by 44.4%~78.5%, and increases the R2 value by 1.3%~132.4%; the MSE value of wheel rail vertical force identification by 36%~75.9%, and the R2 value by 4.4%~87.9%. The proposed method can be applied to data of different working conditions and different noise levels.","PeriodicalId":487259,"journal":{"name":"Journal of Artificial Intelligence Machine Learning and Data Science","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136027156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-06DOI: 10.51219/jaimld/yongjian-sun/12
Wei Wang, Yongjian Sun
W
{"title":"Image Feature Enhancement and Its Application in Fault Diagnosis of Rotating Machinery: A Review","authors":"Wei Wang, Yongjian Sun","doi":"10.51219/jaimld/yongjian-sun/12","DOIUrl":"https://doi.org/10.51219/jaimld/yongjian-sun/12","url":null,"abstract":"W","PeriodicalId":487259,"journal":{"name":"Journal of Artificial Intelligence Machine Learning and Data Science","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135205465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-30DOI: 10.51219/jaimld/yongjian-sun/09
Wei Wang, Yongjian Sun
). Design of Vibration Suppression Simulation for Flexible Manipulator Model. J Artif Intell
{"title":"Design of Vibration Suppression Simulation for Flexible Manipulator Model","authors":"Wei Wang, Yongjian Sun","doi":"10.51219/jaimld/yongjian-sun/09","DOIUrl":"https://doi.org/10.51219/jaimld/yongjian-sun/09","url":null,"abstract":"). Design of Vibration Suppression Simulation for Flexible Manipulator Model. J Artif Intell","PeriodicalId":487259,"journal":{"name":"Journal of Artificial Intelligence Machine Learning and Data Science","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136368335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-12DOI: 10.51219/jaimld/rogerio-adas-pereira-vitalli/08
Rogério Adas Pereira Vitalli, João Manoel Losada Moreira
organization. The robotic system is developed using “Digital Twin” technology, a very realistic virtual modeling scheme that allows interaction with the real world environment. They include equipment and all the steps to carry out the inspection process. The tube wall thickness monitoring system will be used at the Angra 1 nuclear power plant (Brazil).
{"title":"Mathematical Modeling of Digital Twins and Industry 4.0 Technologies for Measuring Pipe Wall Thickness at Angra 1 Nuclear Power Plant","authors":"Rogério Adas Pereira Vitalli, João Manoel Losada Moreira","doi":"10.51219/jaimld/rogerio-adas-pereira-vitalli/08","DOIUrl":"https://doi.org/10.51219/jaimld/rogerio-adas-pereira-vitalli/08","url":null,"abstract":"organization. The robotic system is developed using “Digital Twin” technology, a very realistic virtual modeling scheme that allows interaction with the real world environment. They include equipment and all the steps to carry out the inspection process. The tube wall thickness monitoring system will be used at the Angra 1 nuclear power plant (Brazil).","PeriodicalId":487259,"journal":{"name":"Journal of Artificial Intelligence Machine Learning and Data Science","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136370050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-21DOI: 10.51219/jaimld/martin-wynn/07
Peter Jones, Martin Wynn
Citation
{"title":"Artificial Intelligence and Corporate Digital Responsibility","authors":"Peter Jones, Martin Wynn","doi":"10.51219/jaimld/martin-wynn/07","DOIUrl":"https://doi.org/10.51219/jaimld/martin-wynn/07","url":null,"abstract":"Citation","PeriodicalId":487259,"journal":{"name":"Journal of Artificial Intelligence Machine Learning and Data Science","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135568681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-31DOI: 10.51219/jaimld/moshood-yahaya/06
Moshood Yahaya, Takao Maruyama, Alex Umagba, Sebastian Obeta
- A
{"title":"Maintenance of Aging Offshore Assets - A Digital Twin Approach","authors":"Moshood Yahaya, Takao Maruyama, Alex Umagba, Sebastian Obeta","doi":"10.51219/jaimld/moshood-yahaya/06","DOIUrl":"https://doi.org/10.51219/jaimld/moshood-yahaya/06","url":null,"abstract":"- A","PeriodicalId":487259,"journal":{"name":"Journal of Artificial Intelligence Machine Learning and Data Science","volume":"440 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135950490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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